The error command uses one of two algorithms. If
Monte Carlo Markov Chains are loaded (see chain command) the error range
is determined by sorting the chain values, and then taking a central percentage
of the values corresponding to the confidence level as indicated by <delta fit statistic>.
This is likely to be the faster of the two algorithms.

When chains are not loaded, error’s algorithm
is as follows:

Each indicated parameter is varied, within its allowed hard
limits, until the value of the fit statistic, minimized by allowing all the
other non-frozen parameters to vary, is equal to the last value of fit
statistic determined by the fit
command plus the indicated <delta
fit statistic>, to within an absolute (not fractional) tolerance of <toler>. Note
that before the error command is executed, the data must be fitted. The
initial default values are the range 1—1 and the <delta fit statistic> of 2.706, equivalent
to the 90% confidence region for a single interesting parameter. The number of
trials and the tolerance for determining when the critical fit statistic is
reached can be modified by preceeding them with the stopat keyword. Initially, the values
are 20 trials with a tolerance of 0.01 in fit statistic.

If a new minimum is found in the course of finding the
error, the default behavior is to abort the calculation and then automatically rerun
it using the new best fit parameters. If you prefer not to automatically rerun
the error calculation, then enter nonew at the start of the command string. The
maximum keyword
ensures that error will not be run if the reduced chi-squared of the
best fit exceeds <redchi>.
The default value for <redchi>
is 2.0.

Since there are very many scenarios which may cause an error
calculation to fail, it is highly recommended that you check the results by
viewing the 9-letter error string, which is part of the output from the tclout
error command (see tclout for a description of the error string).
If everything went well, the error string should be “FFFFFFFFF”.

Examples:

Assume that the current model has four model parameters.

XSPEC12> error 1-4

//Estimate the 90% confidence ranges for each parameter.

XSPEC12> error 9.0

//Estimate the confidence range for parameters 1-4 with
delta fit

// statistic = 9.0, equivalent to the 3 sigma range.

XSPEC12> error
2.706 1 3 1. 2

//Estimate the 90% ranges for parameters 1 and 3, and the 1.
sigma

// range for parameter 2.

XSPEC12> error 4

//Estimate the 1. sigma range for parameter 4.

XSPEC12> error
nonew 4

//Same as before, but
calculation will NOT automatically restart if a new minimum is found.

XSPEC12> error stop
20,,3

//Estimate the 1-sigma range for parameter 3 after resetting
the number